Codes
Tick Chart for MetaTrader 4
The presented indicator plots a fully-functional tick chart similar to the standard price charts, with the ability of the analysis using all the MetaTrader features
Articles
Neural Networks in Trading: Detecting Anomalies in the Frequency Domain (CATCH) for MetaTrader 5
The CATCH framework combines Fourier transform and frequency patching to accurately identify market anomalies beyond the reach of traditional methods. Let us examine how this approach reveals hidden patterns in financial data
Neural Networks in Trading: Adaptive Detection of Market Anomalies (Final Part) for MetaTrader 5
We continue to build the algorithms that form the basis of the DADA framework, which is an advanced tool for detecting anomalies in time series. This approach enables effective distinguishing random fluctuations from significant deviations. Unlike classical methods, DADA dynamically adapts to
Neural Networks in Trading: Adaptive Detection of Market Anomalies (DADA) for MetaTrader 5
We invite you to get acquainted with the DADA framework, which is an innovative method for detecting anomalies in time series. It helps distinguish random fluctuations from suspicious deviations. Unlike traditional methods, DADA is flexible and adapts to different data. Instead of a fixed
Neural Networks in Trading: Dual Clustering of Multivariate Time Series (Final Part) for MetaTrader 5
We continue to implement approaches proposed vy the authors of the DUET framework, which offers an innovative approach to time series analysis, combining temporal and channel clustering to uncover hidden patterns in the analyzed data
Neural Networks in Trading: Dual Clustering of Multivariate Time Series (DUET) for MetaTrader 5
The DUET framework offers an innovative approach to time series analysis, combining temporal and channel clustering to uncover hidden patterns in the analyzed data. This allows models to adapt to changes over time and improve forecasting quality by eliminating noise
Neural Networks in Trading: Integrating Chaos Theory into Time Series Forecasting (Final Part) for MetaTrader 5
We continue to integrate methods proposed by the authors of the Attraos framework into trading models. Let me remind you that this framework uses concepts of chaos theory to solve time series forecasting problems, interpreting them as projections of multidimensional chaotic dynamic systems
Neural Networks in Trading: Integrating Chaos Theory into Time Series Forecasting (Attraos) for MetaTrader 5
The Attraos framework integrates chaos theory into long-term time series forecasting, treating them as projections of multidimensional chaotic dynamic systems. Exploiting attractor invariance, the model uses phase space reconstruction and dynamic multi-resolution memory to preserve historical
Neural Networks in Trading: Hybrid Graph Sequence Models (Final Part) for MetaTrader 5
We continue exploring hybrid graph sequence models (GSM++), which integrate the advantages of different architectures, providing high analysis accuracy and efficient distribution of computing resources. These models effectively identify hidden patterns, reducing the impact of market noise and
Neural Networks in Trading: Hybrid Graph Sequence Models (GSM++) for MetaTrader 5
Hybrid graph sequence models (GSM++) combine the advantages of different architectures to provide high-fidelity data analysis and optimized computational costs. These models adapt effectively to dynamic market data, improving the presentation and processing of financial information
Neural Networks in Trading: Two-Dimensional Connection Space Models (Final Part) for MetaTrader 5
We continue to explore the innovative Chimera framework – a two-dimensional state-space model that uses neural network technologies to analyze multidimensional time series. This method provides high forecasting accuracy with low computational cost